Evidence map›Paper›PMID 25637028›Full record

ArticleInternational journal for equity in health2015

Unexplained health inequality--is it unfair?

Yukiko Asada, Jeremiah Hurley, Ole Frithjof Norheim, Mira Johri

Abstract read
In one paragraph

Article in International journal for equity in health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Causal Inference in Health Disparities Research.Annual review of public health · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. The Effect of Ecological Management on Regional Health Inequality.International journal of environmental research and public health · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Using Cost-Effectiveness Analysis to Address Health Equity Concerns.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2017
    Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yukiko AsadaDepartment of Community Health and Epidemiology, Dalhousie University, 5790 University Avenue, Halifax, Nova Scotia, B3H1V7, Canada. yukiko.asada@dal.ca.
Jeremiah HurleyDepartment of Economics and Centre for Health Economics and Policy Analysis, McMaster University, Hamilton, Ontario, L8S4M4, Canada. hurley@mcmaster.ca.
Ole Frithjof NorheimDepartment of Research and Development, Haukeland University Hospital, Jonas Liesvei 65, 5021, Bergen, Norway. ole.norheim@igs.uib.no.
Mira JohriCentre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Tour Saint-Antoine, Porte S03-458, 850, rue St-Denis, Montreal, Quebec, H2X0A9, Canada. mira.johri@umontreal.ca.

Funding

Canadian Institutes of Health Research MPE 124739Canadian Institutes of Health Research MSH 87687
6 · The paper itself

Abstract

introductionAccurate measurement of health inequities is indispensable to track progress or to identify needs for health equity policy interventions. A key empirical task is to measure the extent to which observed inequality in health - a difference in health - is inequitable. Empirically operationalizing definitions of health inequity has generated an important question not considered in the conceptual literature on health inequity. Empirical analysis can explain only a portion of observed health inequality. This paper demonstrates that the treatment of unexplained inequality is not only a methodological but ethical question and that the answer to the ethical question - whether unexplained health inequality is unfair - determines the appropriate standardization method for health inequity analysis and can lead to potentially divergent estimates of health inequity.

methodsWe use the American sample of the 2002-03 Joint Canada/United States Survey of Health and measure health by the Health Utilities Index (HUI). We model variation in the observed HUI by demographic, socioeconomic, health behaviour, and health care variables using Ordinary Least Squares. We estimate unfair HUI by standardizing fairness, removing the fair component from the observed HUI. We consider health inequality due to factors amenable to policy intervention as unfair. We contrast estimates of inequity using two fairness-standardization methods: direct (considering unexplained inequality as ethically acceptable) and indirect (considering unexplained inequality as unfair). We use the Gini coefficient to quantify inequity.

resultsOur analysis shows that about 75% of the variation in the observed HUI is unexplained by the model. The direct standardization results in a smaller inequity estimate (about 60% of health inequality is inequitable) than the indirect standardization (almost all inequality is inequitable).

conclusionsThe choice of the fairness-standardization method is ethical and influences the empirical health inequity results considerably. More debate and analysis is necessary regarding which treatment of the unexplained inequality has the stronger foundation in equity considerations.

Indexed as

Reference StandardsCanadaHealthcare DisparitiesHealth Services AccessibilityHumansModels, TheoreticalSurveys and QuestionnairesUnited States

Identifiers

PMID25637028
PMCPMC4318200

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.